Forecasting Turning Points of Carbon Emissions in Beijing Based on Interpretable Machine Learning

For curbing the global climate crisis, China has set an ambitious target of peak carbon emissions by 2030. Beijing, the capital of China, has implemented a carbon reduction policy since 2012. Using the reduced and generalized forms of the Environmental Kuznets Curve (EKC), we deduce that both the cu...

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Bibliographic Details
Published in:Atmosphere 2023-08, Vol.14 (8), p.1288
Main Authors: Yao, Tianen, Wang, Yaqi, Li, Xinhao, Lian, Xinyao, Li, Jing
Format: Article
Language:English
Subjects:
Air quality management
Algorithms
Carbon
Carbon dioxide
Carbon emissions
Decision trees
Distribution
Economic development
Economic growth
Emissions
Energy consumption
Environmental aspects
Environmental Kuznets Curve
Environmental quality
error correction model
feature selecting
GDP
Genetic algorithms
Global climate
Gross Domestic Product
Hypotheses
Learning algorithms
Machine learning
Performance evaluation
Socioeconomic aspects
Time series
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Summary:For curbing the global climate crisis, China has set an ambitious target of peak carbon emissions by 2030. Beijing, the capital of China, has implemented a carbon reduction policy since 2012. Using the reduced and generalized forms of the Environmental Kuznets Curve (EKC), we deduce that both the cubic EKC and the genetic algorithm-based EKC have an N-shape. The first turning point of the three-order EKC occurs around 2011, demonstrating the effectiveness of the carbon reduction policy. However, the time series model predicts that Beijing will reach the second turning point around 2026, when the gross domestic product (GDP) is about CNY 5000 billion and carbon emissions will begin to increase again. Interpretable machine learning is proposed to explore the socio-economic drivers in carbon emissions, indicating that total energy consumption and GDP contribute the most. Therefore, we should accelerate the upgrading of energy consumption and adjust the industrial structure, thus facilitating Beijing to its peak carbon emissions and achieving carbon neutrality.
ISSN:2073-4433
2073-4433
DOI:10.3390/atmos14081288